Synopsis of a lecture given by Professor Omar Hasan Kasule to the MPH class of Universiti Malaya on Friday 17th November 2006


The concept of the causal triangle (environment, host, and disease) has been used for many years to simplify epidemiological reasoning. Disease risk is a probability. A risk factor is known empirically to be involved in disease causation. Risk indicators are likely to be causes but are not yet confirmed. Data on causes can be obtained from animal or human experiments/observations. Causes may be defined as causative or preventive. A risk factor is described as sufficient when its mere presence will trigger the disease concerned. In practice a sufficient cause refers to a constellation of 2 or more risk factors since most diseases are multi-causal. One disease normally has more than 1 sufficient cause. There are some risk factors that are always present in all sufficient causes of the disease. These are referred to as necessary causes. Causes may be weak or strong. Causes may interact either cooperatively in disease causation (synergy) or act against one another (antagonism). The causal chain or causal pathway is multi-stage. It is initiated by the main risk factor. The final stages are due to promotors. Association of disease with a putative risk factor may be statistically or non-statistical. Statistical association can be causal or non-causal. One disease may have 2 or more co-factors. One disease may have 2 quite different independent causes. One cause leads to 2 different diseases. The criteria of causality are either essential criteria or back-up criteria. The essential causal criteria are four: specificity, strength, time sequence, and biological plausibility. The back-up causal criteria are five: dose-effect relationship, repetition, consistency, evidence from intervention, and experimental evidence.



An exposure is defined as a substance, phenomenon, or event that has a physiological effect, can cause or protect from disease. Exposures may be personal attributes or environmental agents, defined by subjective or objective data, current or past exposures. Exposures can be dichotomous (exposed vs unexposed), ranked according to importance, stratified. Categorization may be based on statistical distributions for example BMI. Exposures may be measured quantitatively or qualitatively. The following are instruments used to measure exposures: questionnaires, personal interviews, biochemical analyses of biological material, physical and chemical analysis of the environment. Measurement of an exposure involves three dimensions: nature of the exposure, the dose, and time. Differential errors in exposure measurement result in a biased odds ratio; the bias remains even of the sample size is increased. Non-differential errors make the odds ratio tend to the null value (attenuation of effect). Non differential error lowers study power and requires a larger sample size to detect a given difference. Measurement errors can be reduced by multiple assessments of the exposure such as repeat assessments of cholesterol. The effect measure can be adjusted to account for the effect of the error. The best approach is to use high quality control measures at the stage of data collection to minimize errors.



Biological determinants are demographic or genetic. Age and gender structure of a population have an impact on mortality and morbidity. Pre-disposition to many diseases is inherited.  Some diseases are known to be genetically-caused while the genetic basis of others is being unravelled. Behavioral determinants are lifestyle and nutrition. Environmental determinants are infections and physical agents such as heat, cold, and radiation. Social determinants are the socio-economic status, occupation, race, ethnicity, and medical care.

Professor Omar Hasan Kasule Sr. November 2006